Journals
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International Journal of Intelligent Systems and Data Science
ISSN: 3143-2328
Building robust, ethical, and scalable data-driven and intelligent systems requires an integrated approach that recognizes the close interdependence between data, analytics, computing infrastructure, and decision-making processes. Advances in data science, machine learning, and information systems increasingly influence decision-making across science, industry, governance, and society, making it essential to address not only technical performance but also reliability, transparency, and long-term sustainability. This includes developing methods that are resilient to data uncertainty, bias, and distributional shifts, as well as designing systems that can adapt to evolving real-world conditions.
Achieving meaningful progress in data science and intelligent systems demands attention to foundational challenges such as data quality, model interpretability, computational efficiency, system scalability, and responsible deployment. Equally important are broader structural considerations, including access to data and computational resources, skills development, data governance, privacy, and the societal implications of data-driven technologies. Addressing these challenges requires collaboration across disciplines, combining theoretical advances with applied research and empirical validation.
The International Journal of Intelligent Systems and Data Science (IJISDS) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from data science, analytics, information systems, machine learning, decision support systems, cloud and distributed computing, and allied domains to deepen understanding of how data-driven and intelligent systems can be designed, evaluated, optimized, and applied responsibly. IJISDS supports research that bridges theory and practice, encouraging contributions that demonstrate both methodological rigor and real-world relevance.
Through its editorial standards and publishing practices, IJISDS actively promotes reproducibility, ethical responsibility, and transparent peer review. The journal also seeks to contribute to broader global priorities by supporting research aligned with sustainable development, digital innovation, responsible data practices, and trustworthy analytics, recognizing the critical role that data science and intelligent systems play in shaping resilient and equitable futures.
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International Journal of Clinical Research and Medical Sciences
ISSN: 3143-2263
The International Journal of Clinical Research and Medical Sciences (IJCRMS) publishes rigorously evaluated research that contributes directly to clinical knowledge and medical science. The journal prioritizes studies with clearly defined research questions, appropriate study design, and transparent analytical methodology, particularly where findings have relevance to diagnosis, treatment, disease progression, or healthcare outcomes.
IJCRMS focuses on clinical research, biomedical investigations, and public health studies grounded in empirical evidence. The journal accepts original research articles, systematic reviews, and structured clinical studies, including observational and retrospective analyses. Case-based submissions are considered only when they provide substantial clinical insight or methodological relevance. Purely speculative, opinion-based, or commercially motivated manuscripts are not within the journal’s scope.
All submissions must demonstrate compliance with recognized medical research ethics, including institutional approval where applicable, informed consent, and full disclosure of conflicts of interest. Manuscripts are evaluated through a double-blind peer-review process with explicit criteria for methodological validity, ethical integrity, and contribution to existing medical literature.
IJCRMS is structured to support reproducible, ethically sound medical research and to serve as a stable scholarly record for clinicians and researchers engaged in evidence-based medical practice.
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International Journal of Adaptive Management and Business Intelligence
ISSN: 3143-7176Building robust, ethical, and scalable organizations requires an integrated approach that recognizes the close interdependence between adaptive management strategies and data-driven business intelligence. As global markets and operational environments become increasingly volatile, it is essential to move beyond static models and embrace systems that prioritize reliability, transparency, and long-term strategic sustainability.
IJAMBI focuses on methods that are resilient to market uncertainty and distributional shifts, specifically designing systems that allow businesses and institutions to adapt to evolving real-world conditions. Achieving meaningful progress in this field demands attention to foundational challenges such as data quality, predictive analytics, computational efficiency, and responsible deployment within corporate and governmental frameworks.
The International Journal of Adaptive Management and Business Intelligence (IJAMBI) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from management science, artificial intelligence, business analytics, and organizational theory to deepen understanding of how intelligent systems can be designed and applied to enhance human decision-making.
IJAMBI supports research that bridges the gap between theoretical frameworks and practical business applications, encouraging contributions that demonstrate both methodological rigor and real-world relevance. Through its editorial standards, the journal promotes reproducibility and ethical responsibility, recognizing the critical role that adaptive systems play in shaping resilient, competitive, and equitable futures.
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International Journal of Artificial Intelligence and Agent Systems
Building robust, trustworthy, and autonomous artificial intelligence systems requires an integrated approach that recognizes the close interdependence between AI models, intelligent agents, computational infrastructure, human oversight, and real-world deployment environments. Advances in artificial intelligence, deep learning, generative AI, large language models, and agentic systems are increasingly transforming science, industry, governance, and society, making it essential to address not only model performance and autonomy but also safety, transparency, reliability, and long-term societal impact. This includes developing AI systems that can reason, learn, collaborate, and adapt under dynamic conditions while remaining aligned with human values, operational constraints, and ethical principles.
Achieving meaningful progress in artificial intelligence and autonomous systems demands attention to foundational challenges such as model robustness, explainability, generalization, alignment, computational efficiency, and responsible deployment. Equally important are broader considerations involving AI governance, safety evaluation, accountability, human-AI collaboration, access to computational resources, and the societal implications of increasingly capable intelligent systems. Addressing these challenges requires interdisciplinary collaboration that combines advances in AI theory, algorithms, architectures, and agent design with rigorous empirical validation and real-world applications.
The International Journal of Artificial Intelligence and Agent Systems (IJAIAS) provides a dedicated scholarly platform to advance these objectives. With a multidisciplinary focus, the journal brings together perspectives from artificial intelligence, deep learning, generative AI, foundation models, large language models, natural language processing, computer vision, reinforcement learning, agentic systems, multi-agent systems, autonomous systems, and trustworthy AI to deepen understanding of how intelligent and autonomous systems can be designed, evaluated, governed, and deployed responsibly. IJAIAS supports research that bridges foundational innovation and practical implementation, encouraging contributions that demonstrate both scientific rigor and real-world impact.
Through its editorial standards and publishing practices, IJAIAS actively promotes reproducibility, transparency, ethical responsibility, and rigorous peer review. The journal also seeks to contribute to broader global priorities by supporting research aligned with responsible AI development, digital transformation, human-centered innovation, AI safety, and trustworthy autonomous systems, recognizing the increasingly significant role that artificial intelligence and agent-based technologies play in shaping resilient, sustainable, and equitable futures.